Wednesday, June 8, 2011

Report back from our survey

Hi all,

I'm here to report back the results of our survey. First, we're very pleased to
report that a number of you guys are happilly running PyPy in production! Most
(97%) of the respondants using PyPy are using it because it's faster, but a
further 26% (respondants could choose multiple answers) are using it because of
lower memory usage. Of users who aren't using PyPy, the most common reason was
C extensions, followed by "Other".

From reading the extra comments section there are a few things we've learned:

Google docs needs a better UI for this stuff

A huge number of people want NumPy and SciPy, it was easily the most
requested C extension (25% of respondants said somthing about NumPy). We've
already blogged on the topic of our plans for NumPy.

Having packages in the various OS's repositories would be a big help in
getting users up and running.

A huge thanks to everyone who responded! Finally, if you're using PyPy in
production we'd love to get a testimonial from you, if you're willing to spare
a few minutes to give us a quote or two please get in contact with us via our
mailing list.

Thanks,
Alex

Hi all,

I'm here to report back the results of our survey. First, we're very pleased to
report that a number of you guys are happilly running PyPy in production! Most
(97%) of the respondants using PyPy are using it because it's faster, but a
further 26% (respondants could choose multiple answers) are using it because of
lower memory usage. Of users who aren't using PyPy, the most common reason was
C extensions, followed by "Other".

From reading the extra comments section there are a few things we've learned:

Google docs needs a better UI for this stuff

A huge number of people want NumPy and SciPy, it was easily the most
requested C extension (25% of respondants said somthing about NumPy). We've
already blogged on the topic of our plans for NumPy.

Having packages in the various OS's repositories would be a big help in
getting users up and running.

A huge thanks to everyone who responded! Finally, if you're using PyPy in
production we'd love to get a testimonial from you, if you're willing to spare
a few minutes to give us a quote or two please get in contact with us via our
mailing list.

@Marko Tasic: If I may ask a question. You wrote that you are using PyPy for highly reliable systems. I know what you mean, but it seems to me that certain features of Python are in contradiction with high reliability. For example, it is in practice impossible to know at compile-time whether you misspelled a variable or parameter in Python source code. My question would be: why are you using a language which has only rudimentary compile-time error detection to implement a high reliability system?

@Maciej Fijalkowski: I will of course do what you ask, but I would like you to point me to at least one blog comment that: (1) Is initially saying that Python/PyPy is *good* for task X, and (2) You or somebody else from the PyPy team wrote "Please take the discussion about X somewhere else".

@⚛ The line might be blurry, but "I'm using PyPy for X" or "I'm not using PyPy for X, because ..." is on topic. While "Python can be used for X" or "Python can't be used for X, because ..." is not on topic. This is a fine line between language implementation (which is PyPy about) and language design (which PyPy is not about, python-dev/python-list/python-ideas mailing lists are about that).